[2024-10-03T08:31:37.501Z] Running test renaissance-movie-lens_0 ... [2024-10-03T08:31:37.501Z] =============================================== [2024-10-03T08:31:37.823Z] renaissance-movie-lens_0 Start Time: Thu Oct 3 08:31:37 2024 Epoch Time (ms): 1727944297520 [2024-10-03T08:31:37.823Z] variation: NoOptions [2024-10-03T08:31:37.823Z] JVM_OPTIONS: [2024-10-03T08:31:37.823Z] { \ [2024-10-03T08:31:37.823Z] echo ""; echo "TEST SETUP:"; \ [2024-10-03T08:31:37.823Z] echo "Nothing to be done for setup."; \ [2024-10-03T08:31:37.823Z] mkdir -p "C:/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_windows/aqa-tests/\\TKG\\output_17279429786926\\renaissance-movie-lens_0"; \ [2024-10-03T08:31:37.823Z] cd "C:/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_windows/aqa-tests/\\TKG\\output_17279429786926\\renaissance-movie-lens_0"; \ [2024-10-03T08:31:37.823Z] echo ""; echo "TESTING:"; \ [2024-10-03T08:31:37.823Z] "c:/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_windows/jdkbinary/j2sdk-image\\bin\\java" --add-opens java.base/java.lang=ALL-UNNAMED --add-opens java.base/java.util=ALL-UNNAMED --add-opens java.base/java.util.concurrent=ALL-UNNAMED --add-opens java.base/java.nio=ALL-UNNAMED --add-opens java.base/sun.nio.ch=ALL-UNNAMED --add-opens java.base/java.lang.invoke=ALL-UNNAMED -jar "C:/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_windows/aqa-tests///..//jvmtest\\perf\\renaissance\\renaissance.jar" --json ""C:/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_windows/aqa-tests/\\TKG\\output_17279429786926\\renaissance-movie-lens_0"\\movie-lens.json" movie-lens; \ [2024-10-03T08:31:37.823Z] if [ $? -eq 0 ]; then echo "-----------------------------------"; echo "renaissance-movie-lens_0""_PASSED"; echo "-----------------------------------"; cd C:/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_windows/aqa-tests/; rm -f -r "C:/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_windows/aqa-tests/\\TKG\\output_17279429786926\\renaissance-movie-lens_0"; else echo "-----------------------------------"; echo "renaissance-movie-lens_0""_FAILED"; echo "-----------------------------------"; fi; \ [2024-10-03T08:31:37.823Z] echo ""; echo "TEST TEARDOWN:"; \ [2024-10-03T08:31:37.823Z] echo "Nothing to be done for teardown."; \ [2024-10-03T08:31:37.823Z] } 2>&1 | tee -a "C:/jenkins/workspace/Test_openjdk11_hs_extended.perf_x86-64_windows/aqa-tests/\\TKG\\output_17279429786926\\TestTargetResult"; [2024-10-03T08:31:37.823Z] [2024-10-03T08:31:37.823Z] TEST SETUP: [2024-10-03T08:31:37.823Z] Nothing to be done for setup. [2024-10-03T08:31:37.823Z] [2024-10-03T08:31:37.823Z] TESTING: [2024-10-03T08:31:48.459Z] Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties [2024-10-03T08:31:50.645Z] NOTE: 'movie-lens' benchmark uses Spark local executor with 4 (out of 4) threads. [2024-10-03T08:31:53.641Z] Got 100004 ratings from 671 users on 9066 movies. [2024-10-03T08:31:53.641Z] Training: 60056, validation: 20285, test: 19854 [2024-10-03T08:31:53.641Z] ====== movie-lens (apache-spark) [default], iteration 0 started ====== [2024-10-03T08:31:53.641Z] GC before operation: completed in 66.380 ms, heap usage 99.002 MB -> 36.932 MB. [2024-10-03T08:32:06.654Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-10-03T08:32:15.372Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-10-03T08:32:24.086Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-10-03T08:32:29.859Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-10-03T08:32:34.520Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-10-03T08:32:39.151Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-10-03T08:32:43.840Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-10-03T08:32:47.522Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-10-03T08:32:47.859Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2024-10-03T08:32:47.859Z] The best model improves the baseline by 14.52%. [2024-10-03T08:32:48.180Z] Movies recommended for you: [2024-10-03T08:32:48.180Z] WARNING: This benchmark provides no result that can be validated. [2024-10-03T08:32:48.180Z] There is no way to check that no silent failure occurred. [2024-10-03T08:32:48.180Z] ====== movie-lens (apache-spark) [default], iteration 0 completed (54357.030 ms) ====== [2024-10-03T08:32:48.180Z] ====== movie-lens (apache-spark) [default], iteration 1 started ====== [2024-10-03T08:32:48.180Z] GC before operation: completed in 99.338 ms, heap usage 128.432 MB -> 50.839 MB. [2024-10-03T08:32:56.927Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-10-03T08:33:04.037Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-10-03T08:33:11.166Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-10-03T08:33:18.276Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-10-03T08:33:21.949Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-10-03T08:33:25.631Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-10-03T08:33:30.297Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-10-03T08:33:33.983Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-10-03T08:33:34.770Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2024-10-03T08:33:34.770Z] The best model improves the baseline by 14.52%. [2024-10-03T08:33:34.770Z] Movies recommended for you: [2024-10-03T08:33:34.770Z] WARNING: This benchmark provides no result that can be validated. [2024-10-03T08:33:34.770Z] There is no way to check that no silent failure occurred. [2024-10-03T08:33:34.770Z] ====== movie-lens (apache-spark) [default], iteration 1 completed (46508.509 ms) ====== [2024-10-03T08:33:34.770Z] ====== movie-lens (apache-spark) [default], iteration 2 started ====== [2024-10-03T08:33:34.770Z] GC before operation: completed in 94.339 ms, heap usage 289.854 MB -> 52.880 MB. [2024-10-03T08:33:43.514Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-10-03T08:33:50.625Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-10-03T08:33:59.395Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-10-03T08:34:05.138Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-10-03T08:34:09.757Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-10-03T08:34:13.461Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-10-03T08:34:18.103Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-10-03T08:34:21.792Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-10-03T08:34:22.538Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2024-10-03T08:34:22.538Z] The best model improves the baseline by 14.52%. [2024-10-03T08:34:22.539Z] Movies recommended for you: [2024-10-03T08:34:22.539Z] WARNING: This benchmark provides no result that can be validated. [2024-10-03T08:34:22.539Z] There is no way to check that no silent failure occurred. [2024-10-03T08:34:22.539Z] ====== movie-lens (apache-spark) [default], iteration 2 completed (47698.938 ms) ====== [2024-10-03T08:34:22.539Z] ====== movie-lens (apache-spark) [default], iteration 3 started ====== [2024-10-03T08:34:22.539Z] GC before operation: completed in 89.275 ms, heap usage 104.653 MB -> 52.972 MB. [2024-10-03T08:34:29.657Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-10-03T08:34:36.819Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-10-03T08:34:45.567Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-10-03T08:34:51.355Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-10-03T08:34:56.008Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-10-03T08:35:00.638Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-10-03T08:35:04.302Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-10-03T08:35:09.030Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-10-03T08:35:09.030Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2024-10-03T08:35:09.030Z] The best model improves the baseline by 14.52%. [2024-10-03T08:35:09.030Z] Movies recommended for you: [2024-10-03T08:35:09.030Z] WARNING: This benchmark provides no result that can be validated. [2024-10-03T08:35:09.030Z] There is no way to check that no silent failure occurred. [2024-10-03T08:35:09.030Z] ====== movie-lens (apache-spark) [default], iteration 3 completed (46522.840 ms) ====== [2024-10-03T08:35:09.030Z] ====== movie-lens (apache-spark) [default], iteration 4 started ====== [2024-10-03T08:35:09.365Z] GC before operation: completed in 96.440 ms, heap usage 72.396 MB -> 51.789 MB. [2024-10-03T08:35:18.098Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-10-03T08:35:25.315Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-10-03T08:35:32.488Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-10-03T08:35:39.595Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-10-03T08:35:43.243Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-10-03T08:35:47.870Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-10-03T08:35:51.557Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-10-03T08:35:56.232Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-10-03T08:35:56.232Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2024-10-03T08:35:56.232Z] The best model improves the baseline by 14.52%. [2024-10-03T08:35:56.232Z] Movies recommended for you: [2024-10-03T08:35:56.232Z] WARNING: This benchmark provides no result that can be validated. [2024-10-03T08:35:56.232Z] There is no way to check that no silent failure occurred. [2024-10-03T08:35:56.232Z] ====== movie-lens (apache-spark) [default], iteration 4 completed (46998.882 ms) ====== [2024-10-03T08:35:56.232Z] ====== movie-lens (apache-spark) [default], iteration 5 started ====== [2024-10-03T08:35:56.232Z] GC before operation: completed in 86.115 ms, heap usage 94.396 MB -> 50.255 MB. [2024-10-03T08:36:04.958Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-10-03T08:36:12.048Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-10-03T08:36:19.157Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-10-03T08:36:26.304Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-10-03T08:36:30.921Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-10-03T08:36:34.639Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-10-03T08:36:39.263Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-10-03T08:36:42.951Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-10-03T08:36:42.951Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2024-10-03T08:36:42.951Z] The best model improves the baseline by 14.52%. [2024-10-03T08:36:43.277Z] Movies recommended for you: [2024-10-03T08:36:43.277Z] WARNING: This benchmark provides no result that can be validated. [2024-10-03T08:36:43.277Z] There is no way to check that no silent failure occurred. [2024-10-03T08:36:43.277Z] ====== movie-lens (apache-spark) [default], iteration 5 completed (46904.967 ms) ====== [2024-10-03T08:36:43.277Z] ====== movie-lens (apache-spark) [default], iteration 6 started ====== [2024-10-03T08:36:43.277Z] GC before operation: completed in 83.229 ms, heap usage 93.739 MB -> 50.207 MB. [2024-10-03T08:36:50.406Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-10-03T08:36:57.516Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-10-03T08:37:06.274Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-10-03T08:37:12.055Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-10-03T08:37:16.670Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-10-03T08:37:20.350Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-10-03T08:37:24.988Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-10-03T08:37:28.661Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-10-03T08:37:28.988Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2024-10-03T08:37:28.988Z] The best model improves the baseline by 14.52%. [2024-10-03T08:37:28.988Z] Movies recommended for you: [2024-10-03T08:37:28.988Z] WARNING: This benchmark provides no result that can be validated. [2024-10-03T08:37:28.988Z] There is no way to check that no silent failure occurred. [2024-10-03T08:37:28.988Z] ====== movie-lens (apache-spark) [default], iteration 6 completed (45738.153 ms) ====== [2024-10-03T08:37:28.988Z] ====== movie-lens (apache-spark) [default], iteration 7 started ====== [2024-10-03T08:37:28.988Z] GC before operation: completed in 88.891 ms, heap usage 126.793 MB -> 50.375 MB. [2024-10-03T08:37:36.185Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-10-03T08:37:44.906Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-10-03T08:37:52.081Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-10-03T08:37:57.876Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-10-03T08:38:02.527Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-10-03T08:38:06.201Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-10-03T08:38:10.843Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-10-03T08:38:14.542Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-10-03T08:38:14.877Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2024-10-03T08:38:14.877Z] The best model improves the baseline by 14.52%. [2024-10-03T08:38:14.877Z] Movies recommended for you: [2024-10-03T08:38:14.877Z] WARNING: This benchmark provides no result that can be validated. [2024-10-03T08:38:14.877Z] There is no way to check that no silent failure occurred. [2024-10-03T08:38:14.877Z] ====== movie-lens (apache-spark) [default], iteration 7 completed (45822.456 ms) ====== [2024-10-03T08:38:14.877Z] ====== movie-lens (apache-spark) [default], iteration 8 started ====== [2024-10-03T08:38:15.205Z] GC before operation: completed in 84.229 ms, heap usage 84.137 MB -> 50.551 MB. [2024-10-03T08:38:22.307Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-10-03T08:38:29.411Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-10-03T08:38:36.574Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-10-03T08:38:43.692Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-10-03T08:38:47.394Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-10-03T08:38:52.029Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-10-03T08:38:55.722Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-10-03T08:39:00.392Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-10-03T08:39:00.392Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2024-10-03T08:39:00.392Z] The best model improves the baseline by 14.52%. [2024-10-03T08:39:00.392Z] Movies recommended for you: [2024-10-03T08:39:00.392Z] WARNING: This benchmark provides no result that can be validated. [2024-10-03T08:39:00.392Z] There is no way to check that no silent failure occurred. [2024-10-03T08:39:00.392Z] ====== movie-lens (apache-spark) [default], iteration 8 completed (45397.391 ms) ====== [2024-10-03T08:39:00.392Z] ====== movie-lens (apache-spark) [default], iteration 9 started ====== [2024-10-03T08:39:00.392Z] GC before operation: completed in 84.611 ms, heap usage 200.878 MB -> 50.556 MB. [2024-10-03T08:39:07.552Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-10-03T08:39:16.276Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-10-03T08:39:23.374Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-10-03T08:39:29.200Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-10-03T08:39:33.847Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-10-03T08:39:37.512Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-10-03T08:39:42.155Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-10-03T08:39:45.876Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-10-03T08:39:45.876Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2024-10-03T08:39:45.876Z] The best model improves the baseline by 14.52%. [2024-10-03T08:39:46.203Z] Movies recommended for you: [2024-10-03T08:39:46.203Z] WARNING: This benchmark provides no result that can be validated. [2024-10-03T08:39:46.203Z] There is no way to check that no silent failure occurred. [2024-10-03T08:39:46.203Z] ====== movie-lens (apache-spark) [default], iteration 9 completed (45529.622 ms) ====== [2024-10-03T08:39:46.203Z] ====== movie-lens (apache-spark) [default], iteration 10 started ====== [2024-10-03T08:39:46.203Z] GC before operation: completed in 84.305 ms, heap usage 101.019 MB -> 50.560 MB. [2024-10-03T08:39:53.322Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-10-03T08:40:00.433Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-10-03T08:40:07.682Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-10-03T08:40:14.787Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-10-03T08:40:18.460Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-10-03T08:40:23.100Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-10-03T08:40:26.774Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-10-03T08:40:31.425Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-10-03T08:40:31.425Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2024-10-03T08:40:31.425Z] The best model improves the baseline by 14.52%. [2024-10-03T08:40:31.755Z] Movies recommended for you: [2024-10-03T08:40:31.755Z] WARNING: This benchmark provides no result that can be validated. [2024-10-03T08:40:31.756Z] There is no way to check that no silent failure occurred. [2024-10-03T08:40:31.756Z] ====== movie-lens (apache-spark) [default], iteration 10 completed (45467.210 ms) ====== [2024-10-03T08:40:31.756Z] ====== movie-lens (apache-spark) [default], iteration 11 started ====== [2024-10-03T08:40:31.756Z] GC before operation: completed in 81.664 ms, heap usage 72.269 MB -> 50.247 MB. [2024-10-03T08:40:38.867Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-10-03T08:40:45.961Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-10-03T08:40:53.094Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-10-03T08:41:00.229Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-10-03T08:41:03.929Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-10-03T08:41:08.605Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-10-03T08:41:12.361Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-10-03T08:41:16.977Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-10-03T08:41:16.977Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2024-10-03T08:41:16.977Z] The best model improves the baseline by 14.52%. [2024-10-03T08:41:16.977Z] Movies recommended for you: [2024-10-03T08:41:16.977Z] WARNING: This benchmark provides no result that can be validated. [2024-10-03T08:41:16.977Z] There is no way to check that no silent failure occurred. [2024-10-03T08:41:16.977Z] ====== movie-lens (apache-spark) [default], iteration 11 completed (45192.492 ms) ====== [2024-10-03T08:41:16.977Z] ====== movie-lens (apache-spark) [default], iteration 12 started ====== [2024-10-03T08:41:16.977Z] GC before operation: completed in 85.852 ms, heap usage 91.656 MB -> 50.479 MB. [2024-10-03T08:41:24.104Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-10-03T08:41:31.241Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-10-03T08:41:38.427Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-10-03T08:41:45.559Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-10-03T08:41:49.301Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-10-03T08:41:52.993Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-10-03T08:41:57.605Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-10-03T08:42:01.285Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-10-03T08:42:01.980Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2024-10-03T08:42:01.980Z] The best model improves the baseline by 14.52%. [2024-10-03T08:42:01.980Z] Movies recommended for you: [2024-10-03T08:42:01.980Z] WARNING: This benchmark provides no result that can be validated. [2024-10-03T08:42:01.980Z] There is no way to check that no silent failure occurred. [2024-10-03T08:42:01.980Z] ====== movie-lens (apache-spark) [default], iteration 12 completed (44991.302 ms) ====== [2024-10-03T08:42:01.980Z] ====== movie-lens (apache-spark) [default], iteration 13 started ====== [2024-10-03T08:42:01.980Z] GC before operation: completed in 100.118 ms, heap usage 319.054 MB -> 50.874 MB. [2024-10-03T08:42:09.104Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-10-03T08:42:16.224Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-10-03T08:42:24.947Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-10-03T08:42:30.707Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-10-03T08:42:35.325Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-10-03T08:42:39.016Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-10-03T08:42:42.704Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-10-03T08:42:46.393Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-10-03T08:42:47.074Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2024-10-03T08:42:47.074Z] The best model improves the baseline by 14.52%. [2024-10-03T08:42:47.074Z] Movies recommended for you: [2024-10-03T08:42:47.074Z] WARNING: This benchmark provides no result that can be validated. [2024-10-03T08:42:47.074Z] There is no way to check that no silent failure occurred. [2024-10-03T08:42:47.074Z] ====== movie-lens (apache-spark) [default], iteration 13 completed (45103.247 ms) ====== [2024-10-03T08:42:47.074Z] ====== movie-lens (apache-spark) [default], iteration 14 started ====== [2024-10-03T08:42:47.387Z] GC before operation: completed in 88.516 ms, heap usage 242.460 MB -> 53.726 MB. [2024-10-03T08:42:54.515Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-10-03T08:43:01.633Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-10-03T08:43:08.791Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-10-03T08:43:15.917Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-10-03T08:43:19.618Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-10-03T08:43:23.300Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-10-03T08:43:27.929Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-10-03T08:43:31.629Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-10-03T08:43:31.629Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2024-10-03T08:43:31.629Z] The best model improves the baseline by 14.52%. [2024-10-03T08:43:31.963Z] Movies recommended for you: [2024-10-03T08:43:31.963Z] WARNING: This benchmark provides no result that can be validated. [2024-10-03T08:43:31.963Z] There is no way to check that no silent failure occurred. [2024-10-03T08:43:31.963Z] ====== movie-lens (apache-spark) [default], iteration 14 completed (44658.452 ms) ====== [2024-10-03T08:43:31.963Z] ====== movie-lens (apache-spark) [default], iteration 15 started ====== [2024-10-03T08:43:31.963Z] GC before operation: completed in 89.800 ms, heap usage 80.920 MB -> 53.898 MB. [2024-10-03T08:43:39.064Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-10-03T08:43:46.194Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-10-03T08:43:54.971Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-10-03T08:44:00.745Z] RMSE (validation) = 0.9919630846870685 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-10-03T08:44:05.363Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-10-03T08:44:09.040Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-10-03T08:44:13.694Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-10-03T08:44:17.379Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-10-03T08:44:17.700Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2024-10-03T08:44:18.022Z] The best model improves the baseline by 14.52%. [2024-10-03T08:44:18.022Z] Movies recommended for you: [2024-10-03T08:44:18.022Z] WARNING: This benchmark provides no result that can be validated. [2024-10-03T08:44:18.022Z] There is no way to check that no silent failure occurred. [2024-10-03T08:44:18.022Z] ====== movie-lens (apache-spark) [default], iteration 15 completed (46017.039 ms) ====== [2024-10-03T08:44:18.022Z] ====== movie-lens (apache-spark) [default], iteration 16 started ====== [2024-10-03T08:44:18.022Z] GC before operation: completed in 92.557 ms, heap usage 233.657 MB -> 50.746 MB. [2024-10-03T08:44:26.783Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-10-03T08:44:32.579Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-10-03T08:44:41.321Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-10-03T08:44:47.127Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-10-03T08:44:50.862Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-10-03T08:44:54.527Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-10-03T08:44:59.224Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-10-03T08:45:03.920Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-10-03T08:45:03.920Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2024-10-03T08:45:03.920Z] The best model improves the baseline by 14.52%. [2024-10-03T08:45:03.920Z] Movies recommended for you: [2024-10-03T08:45:03.920Z] WARNING: This benchmark provides no result that can be validated. [2024-10-03T08:45:03.920Z] There is no way to check that no silent failure occurred. [2024-10-03T08:45:03.920Z] ====== movie-lens (apache-spark) [default], iteration 16 completed (45862.326 ms) ====== [2024-10-03T08:45:03.920Z] ====== movie-lens (apache-spark) [default], iteration 17 started ====== [2024-10-03T08:45:03.920Z] GC before operation: completed in 85.138 ms, heap usage 93.387 MB -> 50.515 MB. [2024-10-03T08:45:11.103Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-10-03T08:45:18.233Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-10-03T08:45:26.951Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-10-03T08:45:32.733Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-10-03T08:45:36.444Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-10-03T08:45:40.118Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-10-03T08:45:44.754Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-10-03T08:45:48.487Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-10-03T08:45:48.862Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2024-10-03T08:45:48.862Z] The best model improves the baseline by 14.52%. [2024-10-03T08:45:48.862Z] Movies recommended for you: [2024-10-03T08:45:48.862Z] WARNING: This benchmark provides no result that can be validated. [2024-10-03T08:45:48.862Z] There is no way to check that no silent failure occurred. [2024-10-03T08:45:48.862Z] ====== movie-lens (apache-spark) [default], iteration 17 completed (44897.568 ms) ====== [2024-10-03T08:45:48.862Z] ====== movie-lens (apache-spark) [default], iteration 18 started ====== [2024-10-03T08:45:49.197Z] GC before operation: completed in 96.276 ms, heap usage 281.652 MB -> 53.979 MB. [2024-10-03T08:45:56.340Z] RMSE (validation) = 3.621968954548761 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-10-03T08:46:03.470Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-10-03T08:46:10.587Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-10-03T08:46:17.708Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-10-03T08:46:21.441Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-10-03T08:46:25.120Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-10-03T08:46:29.743Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-10-03T08:46:33.413Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-10-03T08:46:33.741Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2024-10-03T08:46:33.741Z] The best model improves the baseline by 14.52%. [2024-10-03T08:46:33.741Z] Movies recommended for you: [2024-10-03T08:46:33.741Z] WARNING: This benchmark provides no result that can be validated. [2024-10-03T08:46:33.741Z] There is no way to check that no silent failure occurred. [2024-10-03T08:46:33.741Z] ====== movie-lens (apache-spark) [default], iteration 18 completed (44771.720 ms) ====== [2024-10-03T08:46:33.742Z] ====== movie-lens (apache-spark) [default], iteration 19 started ====== [2024-10-03T08:46:34.080Z] GC before operation: completed in 88.488 ms, heap usage 216.970 MB -> 54.082 MB. [2024-10-03T08:46:41.280Z] RMSE (validation) = 3.6219689545487617 for the model trained with rank = 8, lambda = 5.0, and numIter = 20. [2024-10-03T08:46:48.407Z] RMSE (validation) = 2.1340923218923 for the model trained with rank = 10, lambda = 2.0, and numIter = 20. [2024-10-03T08:46:55.540Z] RMSE (validation) = 1.310518647704681 for the model trained with rank = 12, lambda = 1.0, and numIter = 20. [2024-10-03T08:47:02.717Z] RMSE (validation) = 0.9919630846870686 for the model trained with rank = 8, lambda = 0.05, and numIter = 20. [2024-10-03T08:47:07.331Z] RMSE (validation) = 1.2070175349451324 for the model trained with rank = 10, lambda = 0.01, and numIter = 10. [2024-10-03T08:47:11.021Z] RMSE (validation) = 1.114680167277025 for the model trained with rank = 8, lambda = 0.02, and numIter = 10. [2024-10-03T08:47:15.637Z] RMSE (validation) = 0.922741950338674 for the model trained with rank = 12, lambda = 0.1, and numIter = 10. [2024-10-03T08:47:19.330Z] RMSE (validation) = 0.898064398059034 for the model trained with rank = 8, lambda = 0.2, and numIter = 10. [2024-10-03T08:47:19.330Z] The best model was trained with rank = 8 and lambda = 0.2, and numIter = 10, and its RMSE on the test set is 0.9063252168319611. [2024-10-03T08:47:19.652Z] The best model improves the baseline by 14.52%. [2024-10-03T08:47:19.652Z] Movies recommended for you: [2024-10-03T08:47:19.652Z] WARNING: This benchmark provides no result that can be validated. [2024-10-03T08:47:19.652Z] There is no way to check that no silent failure occurred. [2024-10-03T08:47:19.652Z] ====== movie-lens (apache-spark) [default], iteration 19 completed (45741.176 ms) ====== [2024-10-03T08:47:19.975Z] ----------------------------------- [2024-10-03T08:47:19.975Z] renaissance-movie-lens_0_PASSED [2024-10-03T08:47:19.975Z] ----------------------------------- [2024-10-03T08:47:20.656Z] [2024-10-03T08:47:20.656Z] TEST TEARDOWN: [2024-10-03T08:47:20.656Z] Nothing to be done for teardown. [2024-10-03T08:47:20.656Z] renaissance-movie-lens_0 Finish Time: Thu Oct 3 08:47:20 2024 Epoch Time (ms): 1727945240486